Literature DB >> 19828774

Dose-response modeling of high-throughput screening data.

Fred Parham1, Chris Austin, Noel Southall, Ruili Huang, Raymond Tice, Christopher Portier.   

Abstract

The National Toxicology Program is developing a high-throughput screening (HTS) program to set testing priorities for compounds of interest, to identify mechanisms of action, and potentially to develop predictive models for human toxicity. This program will generate extensive data on the activity of large numbers of chemicals in a wide variety of biochemical- and cell-based assays. The first step in relating patterns of response among batteries of HTS assays to in vivo toxicity is to distinguish between positive and negative compounds in individual assays. Here, the authors report on a statistical approach developed to identify compounds positive or negative in an HTS cytotoxicity assay based on data collected from screening 1353 compounds for concentration-response effects in 9 human and 4 rodent cell types. In this approach, the authors develop methods to normalize the data (removing bias due to the location of the compound on the 1536-well plates used in the assay) and to analyze for concentration-response relationships. Various statistical tests for identifying significant concentration-response relationships and for addressing reproducibility are developed and presented.

Entities:  

Mesh:

Year:  2009        PMID: 19828774      PMCID: PMC3471146          DOI: 10.1177/1087057109349355

Source DB:  PubMed          Journal:  J Biomol Screen        ISSN: 1087-0571


  9 in total

1.  Identification of a cardiac sodium channel insensitive to synthetic modulators.

Authors:  M Mevissen; H Denac; A Schaad; C J Portier; G Scholtysik
Journal:  J Cardiovasc Pharmacol Ther       Date:  2001-04       Impact factor: 2.457

2.  A simple technique for reducing edge effect in cell-based assays.

Authors:  Betina Kerstin Lundholt; Kurt M Scudder; Len Pagliaro
Journal:  J Biomol Screen       Date:  2003-10

3.  Calculating the probability of detection for inhibitors in enzymatic or binding reactions in high-throughput screening.

Authors:  Stephen Buxser; Steven Vroegop
Journal:  Anal Biochem       Date:  2005-05-01       Impact factor: 3.365

4.  Quantitative high-throughput screening: a titration-based approach that efficiently identifies biological activities in large chemical libraries.

Authors:  James Inglese; Douglas S Auld; Ajit Jadhav; Ronald L Johnson; Anton Simeonov; Adam Yasgar; Wei Zheng; Christopher P Austin
Journal:  Proc Natl Acad Sci U S A       Date:  2006-07-24       Impact factor: 11.205

5.  Statistical practice in high-throughput screening data analysis.

Authors:  Nathalie Malo; James A Hanley; Sonia Cerquozzi; Jerry Pelletier; Robert Nadon
Journal:  Nat Biotechnol       Date:  2006-02       Impact factor: 54.908

6.  Quantitative assessment of hit detection and confirmation in single and duplicate high-throughput screenings.

Authors:  Zhijin Wu; Dongmei Liu; Yunxia Sui
Journal:  J Biomol Screen       Date:  2008-01-23

7.  Effects of the mechanism of receptor-mediated gene expression on the shape of the dose-response curve.

Authors:  M C Kohn; C J Portier
Journal:  Risk Anal       Date:  1993-10       Impact factor: 4.000

8.  Evaluation of toxic equivalency factors for induction of cytochromes P450 CYP1A1 and CYP1A2 enzyme activity by dioxin-like compounds.

Authors:  Hiroyoshi Toyoshiba; Nigel J Walker; A John Bailer; Christopher J Portier
Journal:  Toxicol Appl Pharmacol       Date:  2004-01-15       Impact factor: 4.219

9.  Compound cytotoxicity profiling using quantitative high-throughput screening.

Authors:  Menghang Xia; Ruili Huang; Kristine L Witt; Noel Southall; Jennifer Fostel; Ming-Hsuang Cho; Ajit Jadhav; Cynthia S Smith; James Inglese; Christopher J Portier; Raymond R Tice; Christopher P Austin
Journal:  Environ Health Perspect       Date:  2008-03       Impact factor: 9.031

  9 in total
  12 in total

1.  A Data Analysis Pipeline Accounting for Artifacts in Tox21 Quantitative High-Throughput Screening Assays.

Authors:  Jui-Hua Hsieh; Alexander Sedykh; Ruili Huang; Menghang Xia; Raymond R Tice
Journal:  J Biomol Screen       Date:  2015-04-22

2.  Quantitative high-throughput screening for chemical toxicity in a population-based in vitro model.

Authors:  Eric F Lock; Nour Abdo; Ruili Huang; Menghang Xia; Oksana Kosyk; Shannon H O'Shea; Yi-Hui Zhou; Alexander Sedykh; Alexander Tropsha; Christopher P Austin; Raymond R Tice; Fred A Wright; Ivan Rusyn
Journal:  Toxicol Sci       Date:  2012-01-19       Impact factor: 4.849

3.  The Tox21 10K Compound Library: Collaborative Chemistry Advancing Toxicology.

Authors:  Ann M Richard; Ruili Huang; Suramya Waidyanatha; Paul Shinn; Bradley J Collins; Inthirany Thillainadarajah; Christopher M Grulke; Antony J Williams; Ryan R Lougee; Richard S Judson; Keith A Houck; Mahmoud Shobair; Chihae Yang; James F Rathman; Adam Yasgar; Suzanne C Fitzpatrick; Anton Simeonov; Russell S Thomas; Kevin M Crofton; Richard S Paules; John R Bucher; Christopher P Austin; Robert J Kavlock; Raymond R Tice
Journal:  Chem Res Toxicol       Date:  2020-11-03       Impact factor: 3.739

4.  Using weighted entropy to rank chemicals in quantitative high-throughput screening experiments.

Authors:  Keith R Shockley
Journal:  J Biomol Screen       Date:  2013-09-20

5.  Robust Analysis of High Throughput Screening (HTS) Assay Data.

Authors:  Changwon Lim; Pranab K Sen; Shyamal D Peddada
Journal:  Technometrics       Date:  2013-05-01

6.  Optimization and application of median filter corrections to relieve diverse spatial patterns in microtiter plate data.

Authors:  Paul J Bushway; Behrad Azimi; Susanne Heynen-Genel
Journal:  J Biomol Screen       Date:  2011-09-06

Review 7.  Tailored therapeutics based on 1,2,3-1H-triazoles: a mini review.

Authors:  Parteek Prasher; Mousmee Sharma
Journal:  Medchemcomm       Date:  2019-05-14       Impact factor: 3.597

8.  Use of in vitro HTS-derived concentration-response data as biological descriptors improves the accuracy of QSAR models of in vivo toxicity.

Authors:  Alexander Sedykh; Hao Zhu; Hao Tang; Liying Zhang; Ann Richard; Ivan Rusyn; Alexander Tropsha
Journal:  Environ Health Perspect       Date:  2010-10-27       Impact factor: 9.031

9.  A three-stage algorithm to make toxicologically relevant activity calls from quantitative high throughput screening data.

Authors:  Keith R Shockley
Journal:  Environ Health Perspect       Date:  2012-05-10       Impact factor: 9.031

Review 10.  Improving the human hazard characterization of chemicals: a Tox21 update.

Authors:  Raymond R Tice; Christopher P Austin; Robert J Kavlock; John R Bucher
Journal:  Environ Health Perspect       Date:  2013-04-19       Impact factor: 9.031

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